Automated colour segmentation of Tuberculosis bacteria thru region growing: A novel approach

Chayadevi M L, Raju G T
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引用次数: 9

Abstract

Medical image analysis is very challenging due to idiosyncrasies of medical profession. Object recognition with data mining techniques has helped doctors in case of medical emergencies for the image analysis, pattern identification and treatment. Over 180 million people died and more than one third of the population is carrier of Mycobacterium Tuberculosis (TB) bacteria as per the WHO statistics [1-5]. Segmentation of TB from the stained background is very challenging due to noise and debris in the image. In this paper, an automated segmentation of tuberculosis bacterium using image processing techniques is presented. Colour segmentation with region growing watershed algorithm is proposed for the bacterial identification.
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结核菌通过区域生长的自动颜色分割:一种新方法
由于医学专业的特殊性,医学图像分析具有很大的挑战性。物体识别结合数据挖掘技术,帮助医生在医疗紧急情况下进行图像分析、模式识别和处理。据世界卫生组织统计,超过1.8亿人死亡,超过三分之一的人口是结核分枝杆菌(TB)细菌的携带者[1-5]。由于图像中的噪声和碎片,从染色背景中分割TB非常具有挑战性。本文提出了一种基于图像处理技术的结核菌自动分割方法。提出了一种基于区域增长分水岭的细菌识别颜色分割算法。
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